Centricity universal viewer

Manufactured by GE Healthcare

Sourced in United States

Centricity Universal Viewer is a medical imaging software developed by GE Healthcare. It provides a comprehensive platform for viewing and managing medical images from various modalities, including DICOM-compliant images. The software offers tools for image display, manipulation, and analysis to assist healthcare professionals in the interpretation and diagnosis of medical conditions.

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Lab products found in correlation

Prism 9, by GraphPad (1 mentions) Centricity pacs, by GE Healthcare (1 mentions) Centricity enterprise web, by GE Healthcare (1 mentions) Somatom definition flash scanner, by Siemens (1 mentions)

10 protocols using centricity universal viewer

Pelvimetry Measurements for Rectal Cancer Surgery

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Candidate covariates were selected for data collection based on clinical relevance to rectal cancer surgery, as determined by surgeons in the colorectal division and literature review. These variables included sex, age, BMI, tumour height, clinical stage, anterior tumour location, threatened circumferential margins on MRI (≤2mm), neoadjuvant chemoradiation, and history of abdominal surgery or colorectal endoscopic stenting.
Pelvimetry measurements were assessed by two blinded surgeons (JBY and HMT) based on baseline high resolution rectal MRI on the midsagittal (midpoint of anterosuperior aspect of S1) and axial planes using the Centricity Universal Viewer (GE Healthcare, Chicago, IL). In line with previous research [[3 (link), 6 (link)]], midsagittal plane measurements of the inlet length, pubic tubercle height, outlet length, sacral height, and sacral depth were recorded. Axial plane measurements included the interspinous distance at the level of the fovea of the femoral head, and the mesorectal area at the S5 vertebral level (Figure 1). When preoperative MRI was not available, all pelvimetry measurements (except for mesorectal area, which was omitted in these cases) were performed using preoperative computed tomography scans of the midsagittal and axial planes. These measurements of osseous landmarks should be consistent between MRI and computed tomography.

Yuval J.B., Thompson H.M., Fiasconaro M., Patil S., Wei I.H., Pappou E.P., Smith J.J., Guillem J.G., Nash G.M., Weiser M.R., Paty P.B., Garcia-Aguilar J, & Widmar M. (2022). Predictors of operative difficulty in robotic low anterior resection for rectal cancer. Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland, 24(11), 1318-1324.

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Evaluating iRECIST Tumor Assessments

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Four radiologists (L.W., N.J.W., M.W., M.S.) with 5–10 years of expertise in oncologic imaging who routinely perform iRECIST tumor assessments at the institution participated in this study. Before the evaluation, each reader was handed the current iRECIST guidelines [8 (link)], and the key aspects were repeated to ensure an equal level of knowledge for the evaluation. To minimize the influence of the individual reader’s performance, each reader first assessed half of the patients manually and the second half software-assisted. The evaluation scheme is visualized in Figure 1. Each reader was provided with a list indicating which examinations were to be assessed in the respective manner. Computed tomography scans were first reviewed by the respective reader using the institutional picture archiving and communications system (PACS, Centricity Universal Viewer, GE Healthcare™, Chicago, IL, USA). Baseline (BL), follow-up 1 (FU1), and follow-up 2 (FU2) assessments were performed in blocks with at least four weeks in between, thus requiring the readers to refocus at each follow-up time point.

Ristow I., Well L., Wiese N.J., Warncke M., Tintelnot J., Karimzadeh A., Koehler D., Adam G., Bannas P, & Sauer M. (2024). Tumor Response Evaluation Using iRECIST: Feasibility and Reliability of Manual Versus Software-Assisted Assessments. Cancers, 16(5), 993.

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MRI-Guided Tumor Analysis Protocol

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The Centricity Universal Viewer (v. 6.0, GE Healthcare, Chicago, IL, USA) was used for the image analysis and calculation of the ADC values. In the in situ MRI, the ADC_mean, ADC_min, and ADC_max of the whole tumor were determined using an ellipsoidal measuring tool placed to capture as much of the tumor as possible. Fusion imaging allowed us to acquire the coordinates of all inserted biopsy markers on the in situ MRI scan. Consequently, we also determined the ADC values for all biopsy sites. For the measurement, a circular area with a diameter of 2 cm was defined around the coordinate point. This area corresponds to the approximate size of the biopsy punch radius during biopsy collection.

Hettler M., Kitz J., Seif Amir Hosseini A., Guhlich M., Panahi B., Ernst J., Conradi L.C., Ghadimi M., Ströbel P, & Jakob J. (2022). Comparing Apparent Diffusion Coefficient and FNCLCC Grading to Improve Pretreatment Grading of Soft Tissue Sarcoma—A Translational Feasibility Study on Fusion Imaging. Cancers, 14(17), 4331.

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Gallbladder CT Image Dataset

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To create a dataset, only the slices in which the lumen of the gallbladder was visualized were extracted from all CT images, as per the consensus of two surgeons (Y.O., A.H.).
A total of 154 patients (25 patients with GC and 129 patients with AC) were randomly assigned to the training and test groups in equal proportions. The training set consisted of 1,517 images from 112 patients (354 images from 18 patients in the GC group and 1,163 images from 94 patients in the AC group). The test set consisted of the central slices of the gallbladder, resulting in 68 images from 42 patients (11 images of 7 patients in the GC group and 57 images of 35 patients in the AC group).
In this study, the software used was unable to handle Digital Imaging and Communications in Medicine (DICOM) format images, so they were converted to joint photographic experts group (JPEG) format images after adjusting the window level and width to ensure appropriate interpretation using the Centricity Universal Viewer (GE Healthcare, Chicago, IL). Next, the margins were automatically cropped, and the images were automatically resized to 240 × 240 pixels using XnConvert (Gougelet Pierre‐Emmanuel, Reims, France).

Okuda Y., Saida T., Morinaga K., Ohara A., Hara A., Hashimoto S., Takahashi S., Goya T, & Ohkohchi N. (2022). Diagnosing gangrenous cholecystitis on computed tomography using deep learning: A preliminary study. Acute Medicine & Surgery, 9(1), e783.

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Estimating Radiation Dose from X-ray Images

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The DAP in mGy*cm² could be obtained from GE Centricity Universal Viewer in 3067 of 4168 images. The missing values were determined by using simple linear regression (DAP vs body weight) in GraphPad Prism 9.0.0 (GraphPad Software, San Diego, CA, USA), where X is the body weight at the time of imaging:
• Thoracic X-ray: Y = 10 (1.008 × log10 (X) -4.158) ;
• Abdominal X-ray: Y = 10 (1.201 × log10 (X) -4.673) ;

Weiß D., Beeres M., Rochwalsky U., Vogl T.J, & Schlößer R. (2024). Radiation exposure and estimated risk of radiation-induced cancer from thoracic and abdominal radiographs in 1307 neonates. European radiology.

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DICOM Image Data Processing in Clinical Setting

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In clinical situations after exposure, image data are converted into Digital Imaging and Communication in Medicine (DICOM) format for each digital modality system and sent to a hospital server through Centricity PACS (GE Healthcare Japan, Tokyo) [14 ]. In Centricity Enterprise Web (GE healthcare Japan) server, the image data are converted into 8-bit data and delivered to a display terminal in each department. Centricity Universal Viewer (GE Healthcare Japan) was also equipped in the radiology department and all images can be observed with original bit data. Thus, all images in our hospital have 8-bit data. The original DICOM data obtained from each digital modality system in the study, however, had different image bits (Table 1). After obtaining the DICOM data, any post-image processing was not performed and all original data were directly analyzed.

Dashpuntsag O., Yoshida M., Kasai R., Maeda N., Hosoki H, & Honda E. (2017). Numerical Evaluation of Image Contrast for Thicker and Thinner Objects among Current Intraoral Digital Imaging Systems. BioMed Research International, 2017, 5215413.

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Quantitative Lung Segmentation Analysis

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Digital Imaging and Communications in Medicine (DICOM) data were transferred into a picture archiving and communication system (PACS) workstation (Centricity Universal Viewer, version 6.0; GE Medical Systems, Boston, Massachussets, United States). Two radiologists, in consensus (G.G. and D.C., with 5 years and 15 years in thoracic imaging experience, respectively), evaluated the CT scans eligible for segmentation analysis; they then performed CT scan segmentation analysis. The volumetric lung segmentation of each CT scan was performed by using open-source 3D Slicer software (version 4.11.20210226, http://www.slicer.org, accessed on 28 February 2021). Slice-by-slice, a volumetric region of interest (VOI) was manually drawn on mediastinal window scans, with the goal of covering total consolidation volume and avoiding the pulmonary vessels, or bronchi, and cavitations.

Thattaamuriyil Padmakumari L., Guido G., Caruso D., Nacci I., Del Gaudio A., Zerunian M., Polici M., Gopalakrishnan R., Sayed Mohamed A.K., De Santis D., Laghi A., Cioni D, & Neri E. (2022). The Role of Chest CT Radiomics in Diagnosis of Lung Cancer or Tuberculosis: A Pilot Study. Diagnostics, 12(3), 739.

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Temporal Bone CT Imaging for Ossicular Assessment

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Hearing was measured with pure‐tone audiometry (AA‐78; Rion Co. Ltd., Tokyo, Japan). Absent responses to air‐conducted and bone‐conducted sound were coded as 120 dB and 80 dB, respectively.
The biometric characteristics of the ossicular chain of the surgical patients were evaluated on preoperative temporal bone CT images obtained by using the Somatom Definition Flash scanner (Siemens Healthcare, Forchheim, Germany) with acquisition at 0.4‐mm thickness in a suborbitomeatal plane at 120 kV, 250–300 mA. The axial and coronal planes were reconstructed at 0.5‐mm thickness. Both images were stored digitally at Nagoya City University Hospital, Japan.
Digitally‐stored CT images were displayed using the Centricity Universal Viewer (GE Healthcare, Chicago, IL). Precise measurements were made based on consensus between experienced facial nerve specialists (AI and MT) using electronic calipers provided by the EV Insite system (PSP Corporation, Tokyo, Japan), based on methods described in previous reports.¹⁶, ¹⁷ Twelve aspects of each temporal bone CT were recorded by direct measurement, six on axial sections and six on coronal sections.

Inagaki A., Takahashi M, & Murakami S. (2022). Frequency‐dependent hearing outcomes with or without preservation of intact ossicular articulations. Laryngoscope Investigative Otolaryngology, 8(1), 185-191.

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Consensus Reading of MDCT Imaging

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Two experienced radiologists in thoracic imaging (both 6 years) read all MDCT studies in consensus, as commonly done in this field [5 (link), 6 (link)]. Image analyses were undertaken on a workstation with a picture archiving and communication system (Centricity™ Universal Viewer GE Healthcare, Chicago, Illinois). All CT studies were evaluated for the presence of distinctive lung pathologies including non-orthostatic reticulations, ground glass opacifications, consolidations, thickened interlobular septa, pleural and pericardial effusion, emphysema, honey combing, tree-in-bud sign, and pulmonary nodules and cysts, according to the glossary of the Fleischner Society [14 (link)]. In contrast to histologically proven pulmonary metastases, pulmonary nodules referred to the morphologic appearance of discrete rounded opacities up to 3 cm in diameter [14 (link)] without subsequent biopsy. Pulmonary nodules were followed-up according to current Fleischner guidelines [15 (link)]. Additionally, the maximum size of pulmonary nodules and cysts and the regional distribution were recorded for every patient.

Avanesov M., Well L., Laqmani A., Derlin T., Riccardi V.M., Adam G., Mautner V.F, & Salamon J. (2021). Structural alteration of lung parenchyma in patients with NF1: a phenotyping study using multidetector computed tomography (MDCT). Orphanet Journal of Rare Diseases, 16, 29.

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Biplanar Radiograph Measurements for MCGR Patients

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A random assortment of 20 EOS whole spine biplanar radiographs from patients currently undergoing MCGR treatment was utilized for this study. Two patients were represented with two radiographs and one patient with three radiographs at different times. The study population included subjects with idiopathic (n=10), congenital (n=4), neuromuscular (n=1), and syndromic (n=2) scoliosis. At our institution, EOS radiographs are routinely acquired with patients standing relaxed, arms forward, and elbows flexed with the knuckles on clavicle position [18] . Three independent reviewers (two board certified orthopaedic surgeons and one research assistant) performed the measurements independently using Centricity Universal Viewer (GE Healthcare, Chicago, Illionois, USA) and were blinded to patient details. The following parameters were measured:
1. Cobb angle of the main and compensatory curves 2. Coronal balance was defined as the distance (mm) between the C7 plumb line and the Central Sacral Vertical Line (CSVL) 3. T1-12 and T1-S1 length were defined as the distance (mm) from the center of the upper endplate of the T1 vertebra to the center of the upper endplate of the T12 and S1 vertebrae, respectively (Figure 1

Obid P., Yiu K.K.L., Cheung K.M., Kwan K., Ruf M, & Cheung J.P.Y. (2018). Reliability of Rod Lengthening, Thoracic, and Spino-Pelvic Measurements on Biplanar Stereoradiography in Patients Treated With Magnetically Controlled Growing Rods. Spine, 43(22).

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